CFD-DEM study of the effects of food grain properties on drying and shrinkage in a fluidised bed

Jannatul Azmir, Qinfu Hou, Aibing Yu

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Drying is the most important post-harvest processing method for the long-term storage of food grains. Drying and related particle shrinkage are usually determined by various operational conditions and grain properties like grain size, density and initial moisture content. The impact of these food grain properties on drying and shrinkage is investigated by the recently developed computational fluid dynamics-discrete element method drying and shrinkage model. First, particle mixing in a fluidised bed and general drying characteristics are discussed followed by the contribution of different heat transfer modes on fluidised bed drying. The particle scale investigation found that the convective heat transfer is dominant, but the conductive heat transfer becomes important at low air velocities. Then the effect of grain size, density and initial moisture content on drying rate are quantified in terms of drying rate. The drying rate increases exponentially with decreasing grain size, but a slightly smaller drying rate is observed with decreasing initial moisture content and grain density. The shrinkage rate, resembling the drying rate, increases with decreasing grain size or increasing initial moisture content and grain density. Finally, the effects of these food grain properties on the drying quality, quantified by moisture and grain size distributions, are evaluated in this study. The grain scale results revealed that the uniformity of moisture and grain size distributions increases with increasing grain size, decreasing initial moisture content or decreasing grain density. The findings should be useful for a better understanding and control of the drying process in the fluidised bed.

Original languageEnglish
Pages (from-to)33-42
Number of pages10
JournalPowder Technology
Volume360
DOIs
Publication statusPublished - 15 Jan 2020

Keywords

  • CFD-DEM modelling
  • Drying
  • Grain properties
  • Shrinkage

Cite this

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title = "CFD-DEM study of the effects of food grain properties on drying and shrinkage in a fluidised bed",
abstract = "Drying is the most important post-harvest processing method for the long-term storage of food grains. Drying and related particle shrinkage are usually determined by various operational conditions and grain properties like grain size, density and initial moisture content. The impact of these food grain properties on drying and shrinkage is investigated by the recently developed computational fluid dynamics-discrete element method drying and shrinkage model. First, particle mixing in a fluidised bed and general drying characteristics are discussed followed by the contribution of different heat transfer modes on fluidised bed drying. The particle scale investigation found that the convective heat transfer is dominant, but the conductive heat transfer becomes important at low air velocities. Then the effect of grain size, density and initial moisture content on drying rate are quantified in terms of drying rate. The drying rate increases exponentially with decreasing grain size, but a slightly smaller drying rate is observed with decreasing initial moisture content and grain density. The shrinkage rate, resembling the drying rate, increases with decreasing grain size or increasing initial moisture content and grain density. Finally, the effects of these food grain properties on the drying quality, quantified by moisture and grain size distributions, are evaluated in this study. The grain scale results revealed that the uniformity of moisture and grain size distributions increases with increasing grain size, decreasing initial moisture content or decreasing grain density. The findings should be useful for a better understanding and control of the drying process in the fluidised bed.",
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CFD-DEM study of the effects of food grain properties on drying and shrinkage in a fluidised bed. / Azmir, Jannatul; Hou, Qinfu; Yu, Aibing.

In: Powder Technology, Vol. 360, 15.01.2020, p. 33-42.

Research output: Contribution to journalArticleResearchpeer-review

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